Goodness-of-fit tests for generalized logarithmic series distribution

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Abstract

Goodness-of-fit test statistics based on the empirical distribution function (EDF) are considered for the generalized logarithmic series distribution. The α levels of the tests for small or moderate sample sizes are close to the chosen nominal 5% and 10% significance levels. For small or moderate sample sizes, the tests are compared with respect to their simulated power of detecting some alternative hypotheses against a null hypothesis of generalized logarithmic series distribution. The discrete version of the Cramer-von Mises and Anderson-Darling tests are found to be the most powerful pair among the EDF tests. (C) 2000 Elsevier Science B.V. All rights reserved.

Original languageEnglish
Pages (from-to)59-67
Number of pages9
JournalComputational Statistics and Data Analysis
Volume33
Issue number1
DOIs
StatePublished - Mar 28 2000

Keywords

  • Bootstrap
  • Empirical distribution function
  • Monte Carlo simulation
  • Power

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